Global optimization of economic load dispatch in large scale power systems using an enhanced social network search algorithm by Mohamed H. Hassan, Salah Kamel, Francisco Jurado, Umberto Desideri

“…The primary goal is to improve the algorithm's ability to explore global search possibilities while avoiding being trapped in locally optimal solutions. …”
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A Method for Improving the Monitoring Quality and Network Lifetime of Hybrid Self-Powered Wireless Sensor Networks by Peng Wang, Yonghua Xiong

“…Finally, a method based on an improved nutcracker optimizer algorithm is proposed to solve the optimal working sequence of nodes, schedule the “sleep or work” state of nodes, and extend the network lifetime. …”
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Public security patrol path planning recommendation method based on wolf-pack optimization algorithm using DAF and BRS by Dongxing Wang, Gaomin Zhang, Fangbo Wu, Zhiyang Huang, Yiping Chen

“…Firstly, an optimization objective function regarding the public security patrol path planning (S3P-Function) was abstracted from the actual situation; Moreover, this paper proposed an improved wolf-pack optimization algorithm named DAF-BRS-CWOA using Dynamic-Adjustment-Factor(DAF) and Balanced-Raid-Strategy (BRS), and DAF devoted to adjust the overall wolf-pack running strategy by dynamically adjusting the number of airdropped wolves during the stage of Summon-Raid while BRS with symmetric property was to improve both the algorithm’s global exploration as well as the local development capabilities by increasing the number of checking locations, that means not only checking the reverse position of the current wolf, but also the positions generated according to certain rules between the reverse position of the current wolf and the current optimal wolf during the stage of Summon-Raid; Finally, DAF-BRS-CWOA was adopted to optimize S3P-Function, forming a public security patrol path planning recommendation method based on DAF-BRS-CWOA (S3PRM-DAF-BRS-CWOA). 30 independent numerical experiments were conducted on 20 public classical datasets by DAF-BRS-CWOA compared with GA, PSO, WDX-WPOA. …”
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Vehicle Text Data Compression and Transmission Method Based on Maximum Entropy Neural Network and Optimized Huffman Encoding Algorithms by Jingfeng Yang, Zhenkun Zhang, Nanfeng Zhang, Ming Li, Yanwei Zheng, Li Wang, Yong Li, Ji Yang, Yifei Xiang, Yu Zhang

“…In order to optimize the efficiency of mass data transmission in actual operation, this paper presented the text information (including position information) of the maximum entropy principle of a neural network probability prediction model combined with the optimized Huffman encoding algorithm, optimization from the exchange of data to data compression, transmission, and decompression of the whole process. …”
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METAHEURISTIC-AI ENHANCED CUSTOM DEEP LEARNING NETWORK OPTIMIZED WITH SAND CAT SWARM ALGORITHM FOR ORAL CANCER DIAGNOSIS by Vinod Kumar Venkatesan, V Sujatha, Audithan Sivaraman, S Durga Devi, Praveen SR Konduri

“…The CNN architecture is designed to automatically extract discriminative features from images, while the SCSO algorithm fine-tunes crucial hyperparameters such as learning rate, batch size, and dropout rate to enhance model performance. …”
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Optimal design of hollow conductor for high‐speed synchronous motor exploiting adaptive‐sampling radial basis function algorithm by Ruiye Li, Peng Cheng, Hai Lan

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SSM-Net: Enhancing Compressed Sensing Image Reconstruction with Mamba Architecture and Fast Iterative Shrinking Threshold Algorithm Optimization by Xianwei Gao, Bi Chen, Xiang Yao, Ye Yuan

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Detection of water surface targets based on improved Deformable DETR by Pengjiu WANG, Junbin Gong, Wei LUO, Xiao HUANG, Junjie GUO

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Multi-objective recommendation system utilizing a multi-population knowledge migration framework by Liang Chu, Ye Tian

“…Within this framework, we design three distinct optimization paths aimed at enhancing the convergence performance of the multi-objective algorithm and improving the hypervolume value metric of results. …”
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Multi-objective optimization framework for electric vehicle charging and discharging scheduling in distribution networks using the red deer algorithm by Sahbi Boubaker, Habib Kraiem, Nejib Ghazouani, Souad Kamel, Adel Mellit, Faisal S. Alsubaei, Farid Bourennani, Walid Meskine, Tariq Alqubaysi

“…To tackle the optimization problem, a metaheuristic swarm intelligence algorithm, the Red Deer Algorithm (RDA), is utilized to determine the optimal EV charging and discharging timings. …”
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A Framework for Low-Carbon Container Multimodal Transport Route Optimization Under Hybrid Uncertainty: Model and Case Study by Fenling Feng, Fanjian Zheng, Ze Zhang, Lei Wang

“…Subsequently, a multi-strategy improved whale optimization algorithm (WOA) is developed to solve the formulated model. …”
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Enhanced Pure Pursuit Path Tracking Algorithm for Mobile Robots Optimized by NSGA-II with High-Precision GNSS Navigation by Xiongwen Jiang, Taiga Kuroiwa, Yu Cao, Linfeng Sun, Haohao Zhang, Takahiro Kawaguchi, Seiji Hashimoto

“…The improved algorithm considers the dynamic characteristics and real–world operating conditions of the robot, optimizing steering decisions to enhance path tracking accuracy. …”
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FedDyH: A Multi-Policy with GA Optimization Framework for Dynamic Heterogeneous Federated Learning by Xuhua Zhao, Yongming Zheng, Jiaxiang Wan, Yehong Li, Donglin Zhu, Zhenyu Xu, Huijuan Lu

“…Prior to this work, few studies have explored the use of optimization algorithms for hyperparameter tuning in federated learning. …”
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Optimal AC Power Flow with Energy Storage and Renewable Energy: An Efficient RL Algorithm Capable of Handling Equality Constraints by Mingde Liu, Jianquan Zhu, Mingbo Liu

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Comparative Analysis of Some Methods and Algorithms for Traffic Optimization in Urban Environments Based on Maximum Flow and Deep Reinforcement Learning by Silvia Baeva, Nikolay Hinov, Plamen Nakov

“…This paper presents a comparative analysis between classical maximum flow algorithms and modern deep Reinforcement Learning (RL) algorithms applied to traffic optimization in urban environments. …”
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Cost-Effective Optimization of Sizing and Charging Profiles for PHEV Parking Lots in Smart Microgrids Using Harmony Search Algorithm by Mehrdad Ahmadi Kamarposhti, Hassan Shokouhandeh, Emad M. Ahmed, Zaki A. Zaki, Ilhami Colak, El Manaa Barhoumi, Kei Eguchi

“…This paper presents an optimization approach for managing the charging and discharging of electric vehicles (EVs) in parking lots using the Harmony Search (HS) and Differential Evolution (DE) algorithms. …”
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A quasi oppositional forensic based investigation algorithm for optimizing distributed generation placement and sizing in power distribution systems by Binaya Kumar Malika, Vivekananda Pattanaik, Subhasis Panda, Binod Kumar Sahu, Pravat Kumar Rout, Mohit Bajaj, Vojtech Blazek, Lukas Prokop, Stanislav Misak

“…This manuscript addresses these issues by proposing a novel quasi-oppositional forensic-based investigation (QOFBI) algorithm, an evolutionary meta-optimization technique designed to optimize the location and sizing of DGs under various operating conditions, while adhering to system constraints. …”
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Rotation Correction Algorithm Based on Polar Harmonic Fourier Moments and Optimization of Color Image Security Quantization Watermarking Scheme by Yuli Yang, Meiru Jiang, Xiufang Feng, Chenchen Lu, Yongle Chen, Shuang Zhou, Hao Zhang

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Comprehensive optimization of active and reactive power scheduling in smart microgrids by accounting for line transmission losses using genetic algorithm by F.Z. Zahraoui, H.E. Chakir, M. Et-taoussi, H Ouadi

“…The grid-connected SMG consists of photovoltaic (PV) cells, BSS, and residential loads. A Genetic Algorithm (GA)-based method is proposed to optimize power management in three scenarios: (i) active power only (AOM), (ii) active and reactive power without line losses (ARM), and (iii) active and reactive power considering line losses (ARLM). …”
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Multi-Degree Reduction of Said–Ball Curves and Engineering Design Using Multi-Strategy Enhanced Coati Optimization Algorithm by Feng Zou, Xia Wang, Weilin Zhang, Qingshui Shi, Huogen Yang

“…To enhance performance further, we propose a multi-strategy enhanced coati optimization algorithm (MSECOA). This algorithm utilizes a good point set combined with opposition-based learning to refine the initial population distribution, employs a fitness–distance equilibrium approach alongside a dynamic spiral search strategy to harmonize global exploration with local exploitation, and integrates an adaptive differential evolution mechanism to boost convergence rates and robustness. …”
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